Inhibition of Nipah Virus by Defective Interfering Particles.

The error-prone nature of RNA-dependent RNA polymerases drives the diversity of RNA virus populations. Arising within this diversity is a subset of defective viral genomes that retain replication competency, termed defective interfering (DI) genomes. These defects are caused by aberrant viral polymerase reinitiation on the same viral RNA template (deletion DI species) or the nascent RNA strand (copyback DI species). DI genomes have previously been shown to alter the dynamics of a viral population by interfering with normal virus replication and/or by stimulating the innate immune response. In this study, we investigated the ability of artificially produced DI genomes to inhibit Nipah virus (NiV), a highly pathogenic biosafety level 4 paramyxovirus. High multiplicity of infection passaging of both NiV clinical isolates and recombinant NiV in Vero cells generated an extensive DI population from which individual DIs were identified using next-generation sequencing techniques. Assays were established to generate and purify both naturally occurring and in silico-designed DIs as fully encapsidated, infectious virus-like particles termed defective interfering particles (DIPs). We demonstrate that several of these NiV DIP candidates reduced NiV titers by up to 4 logs in vitro. These data represent a proof-of-principle that a therapeutic application of DIPs to combat NiV infections may be an alternative source of antiviral control for this disease.

Measured dynamic social contact patterns explain the spread of H1N1v influenza.

Patterns of social mixing are key determinants of epidemic spread. Here we present the results of an internet-based social contact survey completed by a cohort of participants over 9,000 times between July 2009 and March 2010, during the 2009 H1N1v influenza epidemic. We quantify the changes in social contact patterns over time, finding that school children make 40% fewer contacts during holiday periods than during term time. We use these dynamically varying contact patterns to parameterise an age-structured model of influenza spread, capturing well the observed patterns of incidence; the changing contact patterns resulted in a fall of approximately 35% in the reproduction number of influenza during the holidays. This work illustrates the importance of including changing mixing patterns in epidemic models. We conclude that changes in contact patterns explain changes in disease incidence, and that the timing of school terms drove the 2009 H1N1v epidemic in the UK. Changes in social mixing patterns can be usefully measured through simple internet-based surveys.

The impact of school holidays on the social mixing patterns of school children.

School holidays are recognised to be of great epidemiological importance for a wide range of infectious diseases; this is postulated to be because the social mixing patterns of school children - a key population group - change significantly during the holiday period. However, there is little direct quantitative evidence to confirm this belief. Here, we present the results of a prospective survey designed to provide a detailed comparison of social mixing patterns of school children during school terms and during the school holidays. Paired data were collected, with participants recording their social contacts once during term time and once during the holiday period. We found that the daily number of recorded encounters approximately halved during the holidays, and that the number of close contact encounters fell by approximately one third. The holiday period also saw a change in the age structure of children's social contacts, with far fewer contacts of their own age, but an increase in the number of encounters with adults, particularly older adults. A greater amount of mixing between children at different schools was recorded during the holiday. We suggest, therefore, that whilst infections may spread rapidly within schools during term time, in the holiday period there are increased opportunities for transmission to other schools and other age groups.

Using an online survey of healthcare-seeking behaviour to estimate the magnitude and severity of the 2009 H1N1v influenza epidemic in England.

BACKGROUND: During the 2009 H1N1v influenza epidemic, the total number of symptomatic cases was estimated by combining influenza-like illness (ILI) consultations, virological surveillance and assumptions about healthcare-seeking behaviour. Changes in healthcare-seeking behaviour due to changing scientific information, media coverage and public anxiety, were not included in case estimates. The purpose of the study was to improve estimates of the number of symptomatic H1N1v cases and the case fatality rate (CFR) in England by quantifying healthcare-seeking behaviour using an internet-based survey carried out during the course of the 2009 H1N1v influenza epidemic. METHODS: We used an online survey that ran continuously from July 2009 to March 2010 to estimate the proportion of ILI cases that sought healthcare during the 2009 H1N1v influenza epidemic. We used dynamic age- and gender-dependent measures of healthcare-seeking behaviour to re-interpret consultation numbers and estimate the true number of cases of symptomatic ILI in 2009 and the case fatality rate (CFR). RESULTS: There were significant differences between age groups in healthcare usage. From the start to the end of the epidemic, the percentage of individuals with influenza-like symptoms who sought medical attention decreased from 43% to 32% (p < 0.0001). Adjusting official numbers accordingly, we estimate that there were 1.1 million symptomatic cases in England, over 320,000 (40%) more cases than previously estimated and that the autumn epidemic wave was 45% bigger than previously thought. Combining symptomatic case numbers with reported deaths leads to a reduced overall CFR estimate of 17 deaths per 100,000 cases, with the largest reduction in adults. CONCLUSIONS: Active surveillance of healthcare-seeking behaviour, which can be achieved using novel data collection methods, is vital for providing accurate real-time estimates of epidemic size and disease severity. The differences in healthcare-seeking between different population groups and changes over time have significant implications for estimates of total case numbers and the case fatality rate.

Internet-based surveillance of Influenza-like-illness in the UK during the 2009 H1N1 influenza pandemic.

BACKGROUND: Internet-based surveillance systems to monitor influenza-like illness (ILI) have advantages over traditional (physician-based) reporting systems, as they can potentially monitor a wider range of cases (i.e. including those that do not seek care). However, the requirement for participants to have internet access and to actively participate calls into question the representativeness of the data. Such systems have been in place in a number of European countries over the last few years, and in July 2009 this was extended to the UK. Here we present results of this survey with the aim of assessing the reliability of the data, and to evaluate methods to correct for possible biases. METHODS: Internet-based monitoring of ILI was launched near the peak of the first wave of the UK H1N1v influenza pandemic. We compared the recorded ILI incidence with physician-recorded incidence and an estimate of the true number of cases over the course of the epidemic. We also compared overall attack rates. The effect of using different ILI definitions and alternative denominator assumptions on incidence estimates was explored. RESULTS: The crude incidence measured by the internet-based system appears to be influenced by individuals who participated only once in the survey and who appeared more likely to be ill. This distorted the overall incidence trend. Concentrating on individuals who reported more than once results in a time series of ILI incidence that matches the trend of case estimates reasonably closely, with a correlation of 0.713 (P-value: 0.0001, 95% CI: 0.435, 0.867). Indeed, the internet-based system appears to give a better estimate of the relative height of the two waves of the UK pandemic than the physician-recorded incidence. The overall attack rate is, however, higher than other estimates, at about 16% when compared with a model-based estimate of 6%. CONCLUSION: Internet-based monitoring of ILI can capture the trends in case numbers if appropriate weighting is used to correct for differential response. The overall level of incidence is, however, difficult to measure. Internet-based systems may be a useful adjunct to existing ILI surveillance systems as they capture cases that do not necessarily contact health care. However, further research is required before they can be used to accurately assess the absolute level of incidence in the community.

Pan-European Chikungunya surveillance: designing risk stratified surveillance zones.

The first documented transmission of Chikungunya within Europe took place in Italy during the summer of 2007. Chikungunya, a viral infection affecting millions of people across Africa and Asia, can be debilitating and no prophylactic treatment exists. Although imported cases are reported frequently across Europe, 2007 was the first confirmed European outbreak and available evidence suggests that Aedes albopictus was the vector responsible and the index case was a visitor from India. This paper proposed pan-European surveillance zones for Chikungunya, based on the climatic conditions necessary for vector activity and viral transmission. Pan-European surveillance provides the best hope for an early-warning of outbreaks, because national boundaries do not play a role in defining the risk of this new vector borne disease threat. A review of climates, where Chikungunya has been active, was used to inform the delineation of three pan-European surveillance zones. These vary in size each month across the June-September period of greatest risk. The zones stretch across southern Europe from Portugal to Turkey. Although the focus of this study was to define the geography of potential surveillance zones based on the climatic limits on the vector and virus, a preliminary examination of inward bound airline passengers was also undertaken. This indicated that France and Italy are likely to be at greater risk due to the number of visitors they receive from Chikungunya active regions, principally viraemic visitors from India. Therefore this study represents a first attempt at creating risk stratified surveillance zones, which we believe could be usefully refined with the use of higher resolution climate data and more complete air travel data.